Abstract: Aspects of the present invention provide high-performance indexing for data-intensive systems in which “slicing” is used to organize indexing data on an SSD such that related entries are located together. Slicing enables combining multiple reads into a single “slice read” of related items, offering high read performance. Small in-memory indexes, such as hash tables, bloom filters or LSH tables, may be used as buffers for insert operations to resolve slow random writes on the SSD. When full, these buffers are written to the SSD. The internal architecture of the SSD may also be leveraged to achieve higher performance via parallelism. Such parallelism may occur at the channel-level, the package-level, the die-level and/or the plane-level. Consequently, memory and compute resources are freed for use by higher layer applications, and better performance may be achieved.

Abstract: Aspects of the present invention provide high-performance indexing for data-intensive systems in which “slicing” is used to organize indexing data on an SSD such that related entries are located together. Slicing enables combining multiple reads into a single “slice read” of related items, offering high read performance. Small in-memory indexes, such as hash tables, bloom filters or LSH tables, may be used as buffers for insert operations to resolve slow random writes on the SSD. When full, these buffers are written to the SSD. The internal architecture of the SSD may also be leveraged to achieve higher performance via parallelism. Such parallelism may occur at the channel-level, the package-level, the die-level and/or the plane-level. Consequently, memory and compute resources are freed for use by higher layer applications, and better performance may be achieved.